The current abstract is the result of a collaboration between Unity biotechnology and Tools4 patient As you know, the placebo response is one of the major sources of variability in randomized clinical trials As a result, many trials fail due to a high placebo response. Unfortunately, this is also true in OA studies. However, within Tools4Patient, we have developed a Machine-Learning model named Placebell©™ that can overcome this placebo challenge. This machine -learning
Placebo Response
LEARNING EFFECT & EVALUATION ERROR At Tools4Patient, we are working on the prediction of placebo response and especially the placebo response with endpoints assessing the patients’ pain. As you know, these endpoints represent most of the efficacy endpoints in Osteoarthritis Randomized Clinical Trials. Nevertheless, the assessment of pain is, by nature, subjective and the risk is high
Placebo effect and placebo response are often used interchangeably – despite being two different phenomena. In this blog, we highlight the differences—and why it matters. Placebos are an important part of clinical research. But the impact of placebo use is a long-discussed matter in the biotech and pharmaceutical industry. While helpful in determining drug efficacy, certain factors make using placebos as drug comparators rather complicated. Most will say placebo treatment
Phase II and III trial failure due to unexpectedly large placebo response rates is still all too common. In this blog, we explain what this means and how clinical trials can better manage the placebo response.
Placebos are used in randomized, placebo-controlled controlled trials, in which one group (or more) receives the active treatment and the other group receives the placebo control. This type of study is considered the gold standard of clinical trials for three reasons.
Historically, interpretation of clinical trials relies on “assay sensitivity”, or the sensitivity to detect clinically meaningful differences between endpoints measured in the group of patients given active drug compared to the group of patients given placebo. Assay sensitivity can be influenced by many factors, including the study design, specific endpoints selected, number of clinical sites and, of course, the magnitude of the placebo response.